平流层飞艇动力推进系统的分析与设计

针对平流层飞艇螺旋桨与直流无刷(DC)电动机匹配问题,建立了直流无刷电动机模型和螺旋桨模型;结合匹配设计和直流无刷电动机转速控制,在Simulink中设计了螺旋桨与直流无刷电动机控制系统仿真模型,研究飞艇在0~10m/s巡航速度下动力推进系统控制响应问题;采用图形用户界面(GUI)编写螺旋桨与直流无刷电动机匹配界面,开发了一种螺旋桨与直流无刷电动机匹配软件;得到了飞艇在0~10m/s巡航速度下,螺旋桨工作转速为535~1071r/min,动力推进系统工作效率为0.558~0.593时推进系统匹配设计的工作曲线,为高空螺旋桨与电动机的匹配设计提供了参考依据.      

基于LPV状态空间模型的小型航空煤油二冲程发动机喷油控制策略

为了简化基于平均值模型的喷油控制模型的计算,根据线性变参数(LPV)状态空间模型原理,在平均值模型的基础上建立了LPV状态空间喷油控制模型,利用Matlab/Simulink工具对稳态工况和瞬态工况的喷油脉宽控制模型进行仿真,最后在发动机试验台架上进行试验验证.仿真和试验结果表明:①基于LPV状态空间模型的喷油控制模型能够满足瞬态工况和稳态工况控制的要求,计算的喷油脉宽精度略低于平均值模型,由于LPV状态空间模型计算简单,能够直接应用于控制算法的设计,因此在工程中容易实现.②与插值算法相比,基于LPV状态空间模型的控制策略使发动机的动力输出有所下降,主要是由于模型简化造成进气空气流量减小引起的.      

基于涡方法生成大涡模拟进口条件的数值计算

探索改进涡方法来生成大涡模拟的非定常进口条件.改进方法中,为了避免局部漩涡数量过多或者过少,采用密度分布方式放置漩涡场.并用Langevin方程控制漩涡运动,模拟实验方法中的蜂窝器,使改进后的涡方法生成的脉动速度场更加符合湍流的特征.在已知雷诺平均的流场结果下,利用涡方法产生漩涡场,进而生成能满足大涡模拟所需要的非定常进口流场.为了检验改进后的涡方法在生成脉动速度过程中的效果,在槽道中进行了对比数值试验,并借助于直接数值模拟数据做对比,对比分析槽道进出口的平均速度、涡量以及雷诺应力统计,证明改进后的涡方法在生成大涡模拟进口条件下是非常有效的.      

组合卫星导航系统的快速选星方法

分析了选星数目与几何精度因子(GDOP, Geometry Dilution of Precision)及导航运算量的关系,基于遗传算法提出了一种以满足用户定位精度需求为条件的快速选星方法——快速遗传选星法.根据用户需求确定选星数目初值、选星数目最大值和GDOP阈值,构造选星方案的初始种群,在进化代数上限为1的条件下对种群进行选择、交叉和变异运算,获得初始选星解,根据初始解的GDOP与阈值的关系确定是否依据GDOP最小原则对初始解进行优化,直至满足算法终止条件,输出选星解.仿真结果表明,该算法可以在一次进化之内以不低于92.45%的概率满足GDOP阈值在2.5~6的要求,同时可有效降低54.75%以上的导航运算量.      

三角形机翼参数化有限元网格划分与调整方法

为缩短有限元建模周期,提高三角形机翼结构分析、设计与优化的效率疲,首先,以其满足预定气动性能的几何外形为输入,定义了易用的有限元节点与单元的编号规则;基于可设计的机翼内部构型参数及可变的有限元尺寸参数的设置,引入了翼肋贯穿截止准则以满足任意输入的内部构型的初步判断;借助自定义形状矩阵完成了节点布置与单元生成,进一步通过有限元网格细化完成了开口设置、翼肋贯穿位置修正及桁条建模.然后,基于已建立的有限元网格实现了内外侧副翼翼肋位置的小幅调整及旋转舵面的角度调整,以满足不同飞行状态下结构分析需求.最后,应用PCL语言开发了参数化建模模块,实例表明了方法的有效性和模块可靠性.      

基于LSTM的空间机器人系统惯性张量在轨辨识

在空间机器人抓捕目标的过程中,整个系统的惯性张量会随时间变化且在目标被捕获瞬间发生突变,这会严重影响整体姿态控制的精度。针对以上问题,提出了一种基于长短期记忆（LSTM）的系统惯性张量在轨实时辨识方法。首先,对于目标捕获前后的2个阶段,利用拉格朗日方程建立了空间机器人的动力学模型;然后,基于所建空间机器人模型采用域随机化方法生成足量训练数据,并用其对由LSTM网络与多层全连接网络构建的参数辨识网络进行训练;最后,使用训练好的参数辨识网络对系统惯性张量进行辨识。数值仿真结果表明：所提方法能够精确辨识空间机器人抓捕过程中的系统惯性张量,所研究系统的主惯量平均相对辨识误差小于0.001,惯性积的平均相对辨识误差小于0.01。     

Towards intelligent design optimization: Progress and challenge of design optimization theories and technologies for plastic forming

Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.     

Imaging of target with complicated motion using ISAR system based on IPHAF-TVA

The technique of imaging a target with a complicated motion using an Inverse Synthetic Aperture Radar (ISAR) system is an effective tool in the field of radar signal processing. After the translational compensation, the received signal reflected from the target can take the form of a multi-component Polynomial Phase Signal (m-PPS), and the high quality ISAR image can be provided via the combination between the estimated parameters of the m-PPS and the Range Instantaneous-Doppler technique (RID). For a target with a high maneuvrability, the occurrence of scatterers Migration Through Resolution Cell (MTRC), caused by the rotational movement could be appearing. That is why the variation in the amplitude of the echo during the time of observation cannot be neglected. The purpose of this study is the parameters estimation of the m-PPS signal with order three in the case of the Time Varying Amplitude (TVA). The Improved-version of the Product High-order Ambiguity Function (IPHAF) with TVA is proposed to improve the quality of the ISAR image compared with traditional techniques based on a constant amplitude; the experimental outcomes confirm that the new IPHAF-TVA method presented in this study is an effective technique to make the ISAR image very clear.     

Effect of scavenge port angles on flow distribution and performance of swirl-loop scavenging in 2-stroke aircraft diesel engine

Swirl-Loop Scavenging (SLS) improves the performance of 2-stroke aircraft diesel engine because the involved swirl may not only benefit the scavenging process, but also facilitate the fuel atomization and combustion. The arrangement of scavenge port angles greatly influences in-cylinder flow distribution and swirl intensity, as well as the performance of the SLS engine. However, the mechanism of the effect and visualization experiment are rarely mentioned in the literature. To further investigate the SLS, Particle Image Velocimetry (PIV) experiment and Computational Fluid Dynamics (CFD) simulation are adopted to obtain its swirl distribution characteristics, and the effect of port angles on scavenging performance is discussed based on engine fired cycle simulation. The results illustrate that Reynolds Stress Turbulence model is accurate enough for in-cylinder flow simulation. Tangential and axial velocity distribution of the flow, as well as the scavenging performance, are mainly determined by geometric scavenge port angles α_geom and β_geom. For reinforcement of scavenging on cross-sections and meridian planes, α_geom value of 27° and β_geom value of 60° are preferred, under which the scavenging efficiency reaches as high as 73.7%. Excessive swirl intensity has a negative effect on SLS performance, which should be controlled to a proper extent.     

脉冲星非实时平差的火星探测自主导航模型

针对基于X射线脉冲星观测的火星探测器自主导航,研究了几种不同的实时自适应方法,包括:扩展卡尔曼滤波(EKF),自适应扩展卡尔曼滤波(AEKF)和鲁棒自适应扩展滤波(RAEKF)。首先根据脉冲星导航原理,模拟了观测值:脉冲到达时刻;接着,分别利用扩展卡尔曼滤波,自适应扩展卡尔曼滤波和鲁棒自适应扩展滤波方法估算出探测器的位置和速度;最后,上述几种滤波轨道与STK模拟的标称轨道较差,然后比较它们的滤波精度发现:AEKF和RAEKF的精度相对较高,AEKF的三个轴向滤波位置精度达到:X轴优于100m、Y和Z轴优于30m,优于VLBI技术的km量级,和Doppler技术的精度相当。